System and methods for advanced personalized retail shopping platform

ABSTRACT

A method and graphical user interface in a digital retail shopping system. A client device is in communication with a network. The client device has a display said network connectable to a server and a database of products for purchase. A view of a selected product is presented on the display. A detail of a selected product is retrieved from the database. A detail of the selected product is presented on the display. A personal preferences profile of the user is processed. A comparison parameter is determined, associated with the detail of the selected product and the personal preferences profile of the user. Based on the comparison parameter, an advisory message is generated related to the selected product and the personal preferences profile. The advisory message on the display of the client device is displayed with the view of the selected product and with a detail of the selected product.

FIELD OF THE INVENTION

The present invention is directed to proving an advanced digital retailplatform for personalized shopping. In particular, the disclosurerelates to enabling informed decision making while shopping combinedwith improved personal experience and advisory messaging.

SUMMARY OF THE INVENTION

It is according to one aspect of the disclosure, in a system comprisingat least one communication device in communication with a communicationnetwork, the communication network being connected to a managementserver and at least one database, a computer implemented method istaught for operating the management server to generate personalizedshopping information in an improved manner, the method comprising:

-   -   receiving, from a retail application operating on the        communication device, details relating to behavior of a user of        the communication device;    -   identifying at least one product selected or currently viewed by        the user;    -   retrieving data relating to the product;    -   retrieving data pertaining to the user;    -   generating an advisory message relating to the product and        pertaining to the user; and    -   communicating the advisory message to the communication device.

The method may further comprise the steps:

-   -   receiving a request from the communication device for data        relating to at least one product; and    -   retrieving details relating to at least one comparable product        from an associated product data repository.

Where appropriate, the step of retrieving data relating to the productcomprises accessing data relating to at least one product from a productdata repository.

Where appropriate, the step of generating the advisory messagecomprises:

-   -   analyzing a product preferences profile file;    -   determining a set of comparison parameters; and    -   assigning a weight value for each parameter of said set of        comparison parameters in correlation with the user profile and        personal preferences.

The method may further comprise the steps:

-   -   classifying said set of comparison parameters; and    -   assigning a text (or image or video or other type of) message of        said advisory message.

The method may further comprise the step of ordering selected productsfrom a supplier.

Where appropriate, the supplier is a manufacturer of the product.

The method may further comprise the step of populating a product datarepository by accessing data directly from a manufacturer of theproduct.

It is according to another aspect of the disclosure, in a systemcomprising at least one communication device in communication with acommunication network, the communication network being connected to amanagement server and at least one database, a computer implementedmethod is taught for operating the communication device to providepersonalized shopping information to a user in an improved manner, themethod comprising:

-   -   executing a retail application;    -   selecting or viewing, via the retail application, a product;    -   communicating user behavior to the management server;    -   presenting selected product to a user;    -   receiving from the management server, at least one advisory        message related to the selected product and pertaining to the        user; and    -   presenting at least one advisory message to the user.

Where appropriate, the advisory message may be selected from at leastone of a group consisting of: text messages, images, video files, audiofiles and combinations thereof.

It is according to yet another aspect of the disclosure, a digitalretail shopping system for providing a product consumer with apersonalized shopping experience is provided, the system comprising:

-   -   at least one database in communication with a computing network        and operable to store data relating to a plurality of products        and data pertaining to a plurality of users;    -   a management server in communication with the computing network,        the management server operable to access product-related data        from the database, to access user-pertinent data, and to        generate advisory messages; and    -   a communication device in communication with the management        server via the computing network, the communication device        operable to execute a retail application, to present products to        a user; to identify at least one consumer product selected or        viewed by the user, to communicate user behavior to the        management server, and to receive the advisory messages from the        management server.

The system may further comprise at least one external entity dataresource operable to analyze product related details and configured tomonitor continuously shopping behavior of the product consumer andprovide a classified personalized advisory message associated with theat least one consumer product.

Where appropriate, the communication device may selected from a groupconsisting of a back office client, a mobile client, a web client, athird party client, a set of flat files, reports and combinationsthereof.

Where appropriate, the management server may comprise:

-   -   a data processing engine operable to perform comparability        analysis and generate the advisory message;    -   a personalization engine operable to continuously monitor user        behavior and update a personal preferences profile;    -   a business information engine operable to extract product data        details from the external entity data resources; and    -   a data repository operable to store data pertaining to the at        least one user.

The system may further comprise a prediction engine operable to predictdesired consumer products for purchase by the product consumer.

Where appropriate, the external entity may be selected from a groupconsisting of a retailer entity; product manufacturer entity; and thirdparty commercial entity.

Where appropriate, the data resource may be selected from a groupconsisting of a database; a set of data files; and a web-site.

The system may further comprise a campaign engine operable to allowconnectivity of a third-party entity to provide re-pricing functionalityand defining said third-party entity business strategy.

BRIEF DESCRIPTION OF THE FIGURES

For a better understanding of the invention and to show how it may becarried into effect, reference will now be made, purely by way ofexample, to the accompanying drawings.

With specific reference now to the drawings in detail, it is stressedthat the particulars shown are by way of example and for purposes ofillustrative discussion of the preferred embodiments of the presentinvention only, and are presented in the cause of providing what isbelieved to be the most useful and readily understood description of theprinciples and conceptual aspects of the invention. In this regard, noattempt is made to show structural details of the invention in moredetail than is necessary for a fundamental understanding of theinvention; the description taken with the drawings making apparent tothose skilled in the art how the several forms of the invention may beembodied in practice. In the accompanying drawings:

FIG. 1A is a block diagram showing the main elements of a digital retailshopping platform incorporating a communication system according to afirst embodiment of the invention;

FIG. 1B is a block diagram showing the main elements of a possiblesystem architecture of the digital retail shopping platform;

FIG. 2 is a schematic diagram representing market players potentiallyusing the digital retail shopping platform, focusing on the consumerproduct;

FIG. 3 is a schematic diagram showing an existing concept of shoppingfocusing on a shopping cart and the new alternative concept of shopping,focusing around the consumer product;

FIG. 4A is a flowchart representing selected actions of a possibleshopping flow for a consumer communicating with a backend module on aremote management server via a frontend module application;

FIG. 4B is a flowchart showing a method for the shopping experience viaa digital retail shopping application installed as a frontend module inaccordance with the invention;

FIG. 4C is a flowchart showing a method for the shopping experienceperformed on a remote management server in communication with digitalretail shopping applications in accordance with the invention;

FIG. 4D is a flowchart showing a method for providing the productconsumer with an advisory message for an alternative consumer product;

FIG. 5 is a schematic diagram showing the main elements of a possiblecomparison analyzer module for providing an appropriate advisorymessage;

FIG. 6 is a screen shot for defining the consumer preference profile ofa possible health preferences; and

FIG. 7 is a screen shot showing a presentation of a selected product andassociated alternative product combine with an advisory message.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Aspects of the present invention relate to providing systems and methodsfor efficient shopping experience across a communication network. Inparticular, the disclosure relates to enabling selection of at least oneconsumer product from various repositories associated with variousretailers and product manufacturers, such that the selected consumerproduct is according to consumer personal preferences.

The digital shopping platform may comprise two sub-systems, a frontendsystem and a backend module system, each operable independently andcontinuously to yield a personalized shopping experience. Further, thebackend module system may control the logic of the digital shoppingplatform, by analyzing product related data, product consumer selectionscombined with data pertaining to consumer personal preferences, therebyidentifying the most appropriate advisory message associated to aspecific consumer selection of a product.

The front end module sub-system may comprise a digital shopping web siteor a software application, operable to be installed on various types ofcommunication devices such mobile devices, tablets, laptops, personalcomputers and the like.

The backend module sub-system may comprise a management server incommunication with a data repository comprising at least one database,and the frontend module via a communication computing network. The datarepository system architecture may comprise databases storing differentaspects of data, such as product related data, product consumerpertaining data and further issues of campaign management or dynamicre-pricing as described in FIG. 1B.

In particular, the sub-system of the current disclosure may provideparallel functioning of the backend module sub-system and the frontendmodule sub-system, operable to monitor continuously, the consumerbehavior and adjust the advisory message and the personal preference ofa consumer, while shopping.

DESCRIPTION OF THE EMBODIMENTS

Reference is now made to FIG. 1A showing a block diagram of the mainelements of a digital retail shopping platform 100A incorporating acommunication system 130 according to a first embodiment of theinvention.

The digital retail shopping platform 100A may consist of a frontendmodule installed on a computerized device such as a digital retailshopping software application connectable to a backend module 110 via acommunication network 130. Where appropriate, the computerized devicerunning the digital retail shopping software application may be selectedfrom a group consisting of a tablet 11, a smartphone device 12, a laptopcomputer 13, a display screen 14, a workstation computer 15, a personalcomputer 16, a smart glass (not shown), a smart watch (not shown), smartrefrigeration unit (not shown), other Internet-of-things (IOT) devicesand combinations thereof.

The backend module 110 may include a management server 120 connectableto a data repository 115, directly or via a communication network 130.The data repository 115 may include at least one database for storingdata related to consumer products and data pertaining to the productconsumers. Additionally, various other types of database may be includedto allow connectivity of third parties, for example. Such databases mayallow campaign management, dynamic re-pricing of consumer products andthe like, as described in FIG. 1B.

Reference is now made to FIG. 1B showing a block diagram of the mainelements of a digital retail shopping platform 100B illustrating apossible system architecture including a frontend module 120B and abackend module 140B, according to a first embodiment of the disclosure.

The digital retail shopping platform 100B may consist of a client module120B, a web server 130B, a backend module 140B and a repository module150B.

The client module 120B may be selected from a group consisting of a backoffice interface 122B; a web or a mobile client 124B; a third partyclient 126B; and may further include flat files and reports 128B andcombinations thereof.

The web server 130B may further provide web services 132B operable asweb application components and configured to communicate with openprotocols where HTTP and XML form the basis of the web services.

The backend module 140B comprises a data scraping engine 141B forextracting product related data from commercial web sites; a campaignmanagement engine 142B for allowing external entities (retailers,product manufacturers, brands) to establish and maintain self-productpromotions and lifestyle campaigns within the digital retail shoppingplatform; a dynamic re-pricing engine 143B for allowing retailers todefine retailer specific re-pricing strategy; a data processing engine144B for loading the extracted product data (XML files) into a unifiedcatalog database; a predictions and personalization engine 145B formanaging user interaction and shopping history determining user shoppingbehavior and predicting user preferences of shopping; a premium servicesengine 146B for providing various specific on-demand services; and abusiness information module 147B for providing the tools for determininguser behavior, predictions and market analysis.

It is noted that, where required, the personalization in the digitalshopping platform may be achieved automatically by continuouslymonitoring consumer interactions by collecting, accumulating andanalyzing interactions while shopping.

The gathered information may be updated and stored in real-time in thedata repository of the platform system. Such data may further be used bya business information engine, for example, to allow predictions ofconsumer future shopping preferences.

Web Scraping Engine

The Web Scraping Engine may use a computer software technique ofextracting information from web-sites, such as web-sites of supermarketstores, retailer chains, product manufacturers and the like. WebScraping Engine may comprise a set of complex and comprehensiveinfra-structured Perl scripts, for example which may be designed toprovide robust scraping of target grocery websites' content, forexample. The extracted data from the various sources may beautomatically analyzed and then inserted into structured Product DataXML files. The extracted data may include product related details infoavailable online including products images, prices, attributes and thelike.

Data Processing Engine (DPE):

The Data Processing Engine, may be a set of complex and comprehensiveinfra-structured PHP scripts which may designed to efficiently andrapidly load the extracted product data (XML files) into a unifiedCatalog DB, for example. The Data Processing Engine, may further beoperable to automatically identify similar products originated fromdifferent sources, auto-categorize existing and new products into theright categories, automatically identify and handle data errors,automatically manage and maintain products images.

Dynamic Re-Pricing Engine (DRE):

The Dynamic Re-Pricing may be operable as a third party interface,allowing retailers and product manufacturers to define their ownre-pricing strategy within the digital shopping platform, therebyup-scale and better compete over consumer cart's total priceeffectively.

The Re-Pricing mechanism may be operable to calculate the strategic-salescore of the current potential sale for each of the relevant retailersbased on their real-time strategic parameters values. Accordingly, theDynamic Re-pricing Engine (DRE) 143B may identify the retailer whichobtains the highest strategic-sale score for the current potential saleand calculate the minimal discount value needed to become the cheapestcart price offer among all of the relevant retailers. Furthermore, theDRE 143B may provide the user with a personalized discount coupon to beused for purchasing his cart with the selected retailer.

It is a feature of the dynamic re-pricing mechanism that prices may bepersonalized for each individual transaction. It is noted that pricepersonalization may be implemented for individual items whereappropriate. Additionally or alternatively, price personalization may beimplemented for a collection of items, such as a complete shopping cartof groceries, an outfit of clothes or the like. Regarding cart-centricpricing, it is noted that value of a particular shopping cart may bedetermined according a variety of factors. A valuation function may beprovided to return a strategic-sale score indicating the value of thecurrent transaction. Factors influencing the value of a particularcollection of goods may include purchaser characteristics such asshopping habits, frequency or expected profit from transactions,delivery address and the like. Other factors influencing the value of aparticular collection of goods include transaction characteristics suchas absolute profit of transaction, availability of goods, shelf life ofordered goods, delivery costs and the like. Still other factorsinfluencing the value of a particular collection of goods may beretailer specific.

Accordingly, the Dynamic Re-pricing Engine 143B may analyze thecollection of goods to provide a basket ranking, a strategic-sale scoreor transaction valuation for a collection of goods to a retailer. Theretailer may therefore provide an incentive to the potential purchaserto buy the collection goods from them. Such incentives could take theform of a discount, a coupon, a gift, a free delivery or the like. It isfurther noted that where multiple retailers offer the same goods forsale. The retailers may be encouraged to bid for the transaction.Optionally, the highest discount offered by a retailer may be presentedto the potential purchaser. Alternatively, various discounts andincentives may be presented to a purchaser such that the purchaser canchoose the retailer from which they wish to buy the goods.

Products Predictions and Personalization Engine:

Personalization of the digital shopping platform may be achieved bydefining basic parameters by the product consumer. Additionally oralternatively, the shopping platform may continuously monitor consumerinteractions via the front end software application and by collecting,accumulating and analyzing the consumer interactions. The analysis ofthe personal preferences may be constantly logged into a dedicatedconsumer personal preference file of database and further be analyzedand processed into specific actions to allow applicable changes to theadvisory message, allow product consumer predictions, for example.

It is noted that prediction of the consumer's next desired list ofproducts may allow shortening the consumer's shopping time. Accordinglyproducts may be loaded by a web service which may query the user datadatabase for the specific user's list of products. By way of example,such a list may be accessed via a “Smart Shelf” button (see FIG. 6).

It is further noted that consumer's profile analysis may be based uponaccumulated frontend module software application usage to improvein-application promoted products recommendation engine and thepersonalized importance rank of each available products' attributes pereach user.

Campaign Management Engine (CME):

The Campaign Management Engine mechanism may provide third partyaffiliates (Retailers, Product manufacturers, Lifestylists and Brands)the ability to establish and maintain their own products promotionscampaigns in the digital shopping platform to allow a single productlevel targeting and accuracy.

Campaigns may be generated by a campaigner such as the retailer, productmanufacturer, a lifestylist or the like choosing to promote particularproducts which may be specified or selected according to segments, datesor the like. Accordingly the campaigner may provide a tag line for aproduct such as “more flavor”, “less sugar”, “extra points” or the like.Such tag lines could be targeted to a particular purchaser, for example,a purchaser who has indicated a preference for low fat products, may beshown an appropriate tag line such as “fewer calories” whereas anotherpurchaser who has shown a preference for less salt may be shown analternative tag line such as “no added salt” or the like. Other contentmay be provided such as product reviews or purchase advice may beprovided by campaigners such as lifestylists.

Campaigns may furthermore provide alternative product suggestions. Forexample a purchaser of one product may be presented with an alternativeproduct, so for example a purchaser may be presented with a suggestedoven baked variety of chip alongside a fried chip, or perhaps a ricecracker rather than a bran cracker. Sponsored campaigns may be indicatedto a purchaser by the use of indicators such as colored spots or thelike.

Such alternative product suggestions may be presented variously, forexample, a small icon representing a suggested alternative product mayenter from the side of the screen where it replaces the productoriginally indicated adjacent to the currently selected product.

It is further noted that a third party lifestyle campaign may be enabledby a lifestylist. Users may choose to adhere a particular lifestylist,or lifestyle. This may be enabled via a social network where members ofthe social network may choose to follow the suggestions of a particularcelebrity stylist, friend, link or contact.

Where required, the lifestylist introducing personalized parameters tobe used in selection of a suggested product. For example, a weightmanagement campaigner may provide a point ranking for various food itemsand a purchaser may choose to have this parameter indicated while goodsare being selected. It is further noted that lifestyle parameters may beused by selection algorithms for generating alternative productsuggestions, as required.

It is noted that the system architecture particulars of the digitalretail shopping platform 100B is presented only by way of example andfor purposes of illustrative discussion. Other alternative systemdesigns may be valid.

Reference is now made FIG. 2 is showing a schematic diagram 200representing market players potentially using the digital retailshopping platform, focusing on the consumer product.

The schematic diagram 200 represents the main components of interactionsin the digital retail shopping platform, putting the consumer product210 in which a product consumer 220 is interested in the center.

Additionally, there are other market players of importance with respectto the digital retail shopping platform notably the product manufacturer230, retailer 240, as well as third party advisors 250, lifestylists 260and the like.

A third party advisor 250 may be a friend, contact or link such as acelebrity or the like that a user has opted to follow. Such a thirdparty 250 may offer purchasing advice to the user.

Similarly, a lifestylist 260 may provide purchasing advice to the users.For example, a health advisor, such as a dietitian may provide healthadvice to shoppers purchasing food goods, for example. In otherapplications a fashionista, celebrity or clothes stylist may suggestsuitable clothes and outfits to be selected by a consumer.

Reference is now made FIG. 3 is showing the concept representing mostcommon shopping experience which is primarily “cart” centric focusing onthe shopping cart of the consumer and mainly referring to the price asthe decisive parameter and the new alternative concept of shopping ofthe current disclosure, focusing around the consumer product and theproduct itself.

The cart centric shopping experience may include a commercial web siteor a software application 310 used by a product consumer 320, creating asingle transaction 330 for transferring a list of consumer products froma supermarket, for example into a consumer cart. Accordingly, pricepersonalization may be implemented for a collection of items allowingcart-centric pricing in keeping with various factors such as purchasercharacteristics, transaction characteristics as well as retailerspecific factors.

Additionally or alternatively, the current disclosure introduces aproduct centric shopping concept based upon consumer interactions forevery specific product. The user application 350 may create multiplemini-transactions 330 a, 330 b through 330 n where each mini-transactionmay be associated with a single product to answer the personalpreferences of a product consumer.

For example, mini-transaction 330 a may be generated to allow theproduct consumer 360 to select a specific product 312, which may be theoriginal product the consumer requested, or may be a comparable productselected in response to an advisory message received, offering apreferred alternative product.

It is noted that when reference is made to a better or preferredproduct, such preferences are considered from the consumer perspectiveaccording to personal preferences.

Suggested products may include recommended alternative brands of thesame goods which may be preferred because of price, taste or otherpreference. Other suggested products may include recommendations ofalternative goods which may be preferred such as a gnocchi alternativeto pasta or a cracker alternative to bread, for example. Good may beassociated with related product reviews or lifestyle related contentoffering advice to the consumer.

Reference is now made to the flowchart of FIG. 4A representing selectedactions of a method 400A illustrating a possible shopping flow for aconsumer communicating with a backend module running on a remotemanagement server via a frontend module application. The method 400 isoperable for enabling a consumer to experience efficient shoppingprocess online according to personal preferences.

The method 400A is described spanning two nodes of a distributed systemarchitecture, based upon a centrally managed server controllingcommunication requests between a frontend module and a backend moduleconnectable to a repository comprising at least one database for storingat least consumer preferences and various consumer products and relateddata.

It is noted that FIGS. 4B-D further describe the functionality ofassociated methods.

The method 400A may include executing a retail shopping softwareapplication on a client device such as a smartphone, a tablet, a laptop,a personal computer and the like—step 420A; and setting up the consumerprofile with related personal preferences—step 422A, for example, byaccessing of health and preferences indicators of the consumer perhapsby integrating with external sources such as smartphone health softwareapplications, smart watches and the like.

Optionally, the consumer profile may include various groupings ofpersonal preferences in separate categories.

Furthermore, the method includes searching for a requested productpertaining to the consumer—step 424A, or optionally browsing a list ofproducts pertaining to the consumer. Accordingly, the product currentlyselected by the consumer may be identified—step 426A and the detailsrelating to the selected product may be retrieved from the backendmodule—step 428A.

The method 400A on the backend module side may start by receiving arequest for details related to selected consumer product, from theretail shopping software application—step 430A, where the request mayinclude, where appropriate, consumer and product identification data ordata pertaining to groupings or categories. Thus allowing the retrievingof details related to the product from the product associateddatabase—step 432A and sending to the retail shopping softwareapplication the retrieved related data details—step 434A, in astructured data message.

Accordingly, on the frontend module side the received data message maybe presented for the requested product—step 436A. On the backend moduleside, the consumer's personal preferences profile maybe processed—step436A. By processing the personal profile, comparison parametersassociated with the details related to the requested product may bedetermined—step 440A, and weights for each comparison parameters may beassigned—step 442A and assigning a value for each such parameters—step444A, possibly according to analysis of consumer's personal preferences.The comparison parameters may be automatically generated orclassified—step 446A; and a first generated or classified advisorymessage may be sent to the frontend module user application—step 448A.

It is noted that the classified advisory message may include text,tabulated message, related image, video content, audio content and thelike.

The method may continue with the retail shopping software applicationpresenting the advisory message to the consumer—step 450A therebyallowing consumer decision for the desired product—step 460A.

Reference is now made to the flowchart of FIG. 4B representing selectedactions of a method 400B illustrating a possible shopping interactionsof a consumer communicating with a backend module, via a digital retailshopping software application in accordance with the invention.

The method 400B may include executing a retail shopping softwareapplication on a client device such as a smartphone, a tablet, a laptop,a personal computer and the like—step 410B, as the frontend setting ofthe platform. The application may be used to browse to select arequested product from a list—step 420B. Alternatively, or additionallya user may search for the requested product by typing in searchparameters or by activating a search by voice via a voice recognitionmodule. Accordingly, the requested product may be presented alongsiderelated product details pertinent to the consumer—step 430B.Furthermore, an advisory message may be received advising the user ofoptions for alternative brands or products relating to the requestedproduct selected by the consumer—step 440B. Accordingly, the advisorymessage for the alternative product may be presented—step 450B, forexample as a text message or the like. Additionally or alternatively,the advisory message may take various forms such said message text,image, video clip, audio session and the like. Accordingly, the consumermay select the specific product—step 460B; and the selection may becommunicated to the backend module—step 470B.

It is noted that, the shopping platform may continuously monitor andperform comparable analysis of consumer decisions upon receiving theadvisory message. This may serve to provide further classified messages,or updating consumer preferences profile, to allow for improvingadvisory messages in future purchases.

Reference is now made to the flowchart of FIG. 4C representing selectedactions of a method 400C illustrating possible shopping interactions onthe backend module while communicating with a frontend module inaccordance with the invention.

The method 400C may include compiling a dataset related to consumerproducts—step 410C; setting the consumer personal preferences—step 420C;presenting a selected product to a consumer—step 430C; presenting tosaid consumer an advisory message for an alternative consumerproduct—step 440C; and receiving a consumer selection of the desiredproduct—step 450C, reflecting the consumer decision.

It is noted that further examples for steps 430C and 440C are elaboratedin FIG. 4D, particularly describing the step related to the advisorymessage and associated with an alternative consumer product, if thesystem analysis, based upon alternatives pertinent to consumer personalpreference.

Where appropriate, consumer behavior may be monitored—step 460C whichmay allow the effectiveness of the advisory message on consumer shoppingdecisions to be assessed. Accordingly, the user database may beupdated—step 465C. Optionally, if the initial advisory message was noteffective, based upon system analysis, an additional advisory messagemay be sent to the product consumer—step 470C. Accordingly, resultingorders may be submitted to the product manufacturer—step 470C.

Reference is now made to the flowchart of FIG. 4D representing selectedactions of a method 400D illustrating the flow for providing an advisorymessage, generated by the backend module, for an alternative product inaccordance with the invention.

The method 400D may include identifying the product selected by theconsumer—step 410D; retrieving an alternative product by the consumerrelated to previously selected product—step 420D; getting the relevantpersonal preferences segment from the consumer preferences profile fileassociated with the category or grouping of the product—step 430D;generating a set of comparison parameters based upon selectedproduct—step 440D; assigning a weight value for each element defined ofthe comparison parameter set—step 450D; performing a comparison analysisbetween the selected consumer product and suggested alternativeproducts—step 460D; classifying the comparison results for each elementof the comparison parameters set—step 470D, according to its assignedweight value; generate an advisory message for the highest classifiedelement—step 480D.

It is noted that the advisory message may be a text message, an image, atabulated message group, a video clip, an audio clip and the like.

It is further noted that classified advisory message may refer topersonal preferences or lifestyle choices such as low fat, low calories,no sugar, organic product, gluten free diet, vegan diet and more, asdescribed, for example in FIG. 7.

Regarding lifestyle choices, it is noted that suggestions and messagesmay be generated according to third-party product grading parameters,such as point systems determined by third parties.

The above listed set of preferences is to be considered as an examplefor illustrative purposes referring to a shopping platform associatedwith grocery food. Other preferences may be generated, as will occur tothose of the art where the line of product is different, such asfashion, electronics and computers, agricultures, home appliances andthe like.

Reference is now made to FIG. 5 showing a schematic diagram of the mainelements of a comparison analyzer module for computing an appropriateadvisory message.

The comparison analyzer module may include the comparison analyzerengine 510 connectable to the backend repository 520 via an inputinterface layer 512 and outputting analysis results via an outputinterface layer 514. The backend repository 520 may further includespecific databases such as a user database 522 holding user specificdata, optionally in a form of user profile files and product database(one or more) associated with specific product manufacturers orretailers for example holding data related to the various products, suchas 532 holding data related to the selected product and 534 holding datarelated to possible alternative products.

The comparison analyzer engine 510 may generate a set of comparisonparameters a, b through n according to the specification of the relevantsegment of the personal preferences information of the product consumer.Each comparison parameters may further be assigned with a weight valueindicating the level of importance of the comparison parameter withrespect to consumer personal preferences.

It is a particular feature of the comparison analyzer engine 510 thatthe set of parameters is open. Accordingly, parameters may be added bythird parties such as lifestylists or the like who may introduceadditional or alternative grading systems based upon their own lifestylephilosophies and models.

Sample Screen Shots:

Reference is now made to FIG. 6 showing an illustrative screen shot 600of a mobile device application for defining the consumer preferenceprofile of a possible health personal preferences for a product consumerrelated to a shopping platform for grocery products, pharmacy relatedproducts, books and the like.

The screen shot 600 of a consumer personal preferences profile mayinclude a header section 610, a profile body section 620 and a bottomsection 630. It is noted that the sections, as brought hereinabove, areby way of example and should not be considered as limiting. Othersections may be added or omitted to suit requirements.

The header section 610 may include general mobile device informationsuch as the mobile company, Wi-Fil connection, time, battery level andthe like. The header 610 may further include title elements andcurrently logged in user name.

The body section 620 may include a list of selectable preferences suchas Low Calories, Low Fat, Organic Product, Vegan Diet, Vegetarian Diet,Gluten Free Diet, Low Carbohydrate, Low Sugar, Low Sodium and LowProtein. Each selectable preference parameter may be attached with acontrol element such as 622, operable to set on a parameter or set off,by simply dragging the control element to the desired position.

The bottom section 630 may include a set of controls such as a Catalogbutton to allow accessing product related data, a Shelf button, a Cartbutton to allow viewing shopping status, and a user button to allowdisplaying various personal account parameters.

It is noted that this list of preferences as brought hereinabove is byway of example and should not be considered as limiting. Otherpreferences may be added or omitted to suit requirements.

Reference is now made to FIG. 7 showing an illustrative screen shot 700of a mobile device shopping platform application of a currently viewedproduct and associated alternative products combined with an advisorymessage based upon analyzing personal preferences and product comparableparameters.

It is of particular importance that the software application is operableto allow for easy switching between product browsing mode and detailsviewing mode. The product consumer may browse through various productsof a specific category or shelf by simply scrolling or swiping. Stoppingof scrolling or swiping to enable selection of a product of interest forviewing, may present automatically the currently desired product view atthe center coupled with associated product details with no need for anyspecific user action. Additionally, and in parallel, the productcomparison mechanism may be activated in the background, based uponconsumer personal preference profiles to present alternative comparableproducts to the left or right of the viewed product.

Optionally, presenting of an alternative product may use variousanalysis mechanisms, such as an app-based mechanism performing analysisbased upon product availability and adaptability with user preferences.Additionally or alternatively an analysis may be provided incorporatinginput from an advertising mechanism which may provide a weighting factorto sponsored products. Where appropriate, indication may be provided toinform the user whether a recommended alternative product is generatedby the app-based mechanism or the advertising mechanism. For example, agreen dot may indicate that the alternative comparable product presentedis generated by the app based mechanism perhaps based upon existingproduct availability and according to personal preferences, whereas anorange dot may be used to indicate that a pre-paid alternativecomparable product offering, according to personal preferences has beengenerated using the advertising mechanism.

It is noted that a product retailer/manufacturer/advertiser may beallowed to select products for promotion, while the system may beoperable to combine the desired promotion with consumer personalpreferences.

The screen shot 700 captures a particular instant during shopping flowfor a specific consumer product 722 viewing a desired product ofinterest at the moment that scrolling has been stopped for example, andmay include a header section 710, a profile body section 720 and abottom section 730.

The header section 710 may include general mobile device information(not shown) such as the mobile company, Wi-Fi connection, time, batterylevel and the like. The header 710 may particularly include the messagearea 712, displaying the advisory message for an alternative productcomparable to a currently viewed consumer product. It is noted that theadvisory message may be presented as a text message, a video, an image,an audio message or the like as required.

The body section 720 may include a currently viewed product 722, productdetails sub-section 725 and two alternative products of the sameviewable category, being presented based upon the comparison analysis.As appropriate, the consumer product 724 may represent an alternativecomparable product “A” of the viewable shelf/category, where product 724may be generated by an analysis of product availability and adaptabilitywith user preferences for example and marked accordingly with a greendot. Further, the consumer product 726 may represents anotheralternative comparable product “B” of the viewable shelf/category, whereproduct 726 may be generated by an advertising mechanism and mayindicate a sponsored product and may be marked accordingly for examplewith an orange dot.

Additionally to the details viewed product sub-section 725, the pricingdetails associated with product 722 may be presented. The cheapestretailer price may be associated with a first manufacturer 714,providing its pricing and the most expensive retailer price may beassociated with a second manufacturer 716. It is noted that the pricingsection, proving retailers' pricing of the viewable product may beclicked/scrolled/swiped to view the whole range of pricing of allretailers.

The “Add to Cart” button 718 allows the consumer to move the preferredconsumer product to consumer cart, finalizing the shopping flow for thecurrent product. Alternatively or additionally, plus and minus icons maybe used to add or remove items from a consumer cart.

It is particularly noted that a set of icons 725 are providedrepresenting product details based upon indications of consumer personalpreferences associated with the group of currently selected consumerproduct, such as Calories indications, Proteins indications, UsersRanking, Lifestyle Rankings, Kosher Certification, Religious DietaryLaws and the like. It is noted that the list of product details may beclicked/scrolled/swiped up and down or sideways to view the variousavailable details.

Additionally or alternatively, the presented product details mayindicate to a user personalized social ranking of a particular product.For example, the user may be presented with an indication of how popularthe product is amongst his/her own social group. To this end, the numberof friends who liked or purchased the product may be presented.Furthermore where the user's friends have provided a review, a comment,a rank or a grade pertaining to the particular product, this may bepresented alongside the product. Accordingly, a user feedback engine maybe provided to receive such social feedback from users.

The bottom section 730 may include a set of controls such as a Catalogbutton to allow accessing product related data, a “Shelf” button toallow viewing a virtual shelf containing products of the samecategory/group, a Cart button to allow viewing the list of collectedproducts in the virtual cart, the products availability, productsprices, promos and delivery cost and the total of the cart at eachavailable retailer, and a user button to allow displaying variouspersonal account parameters.

It is also noted that the advisory message, illustrated hereinabove as atextual message may be presented in various other forms such as image,tabulated data, video clip, audio clip and the like.

It is according to another aspect of the current disclosure that theproducts are categorized and presented in a readily navigable mannerenabling a user to easily view and select multiple products especiallyon small screens.

Accordingly, it has been surprisingly found that a particularly suitablecategorization may be a hierarchical tree structure having multiplelevels where each level has a maximum of four sibling nodes. Using sucha structure a user is able to make a simplified choice at each levelallowing faster and more precise navigation to a product of choice.

It is noted that in contradistinction to the three level categorizationtraditionally used by online stores, the current structure does not havetoo many nodes that need to be scrolled through at each level. Rather,the current structure allows a simple and clear screen to be presentedat each level at which a user can select one of only four options. Thispresentation has been found to be more efficient, and enables the userto target the required product with greater precision, particularly onsmaller screens.

In certain embodiments, the hierarchical structure may itself bepersonalized for a particular user such that categories may begenerated, filters applied and the order or selection of nodes at eachlevel prioritized and reordered according to the user's personal usage.

Technical and scientific terms used herein should have the same meaningas commonly understood by one of ordinary skill in the art to which thedisclosure pertains. Nevertheless, it is expected that during the lifeof a patent maturing from this application many relevant systems andmethods will be developed. Accordingly, the scope of the terms such ascomputing unit, network, display, memory, server and the like areintended to include all such new technologies a priori.

As used herein the term “about” refers to at least ±10%.

The terms “comprises”, “comprising”, “includes”, “including”, “having”and their conjugates mean “including but not limited to” and indicatethat the components listed are included, but not generally to theexclusion of other components. Such terms encompass the terms“consisting of” and “consisting essentially of”.

The phrase “consisting essentially of” means that the composition ormethod may include additional ingredients and/or steps, but only if theadditional ingredients and/or steps do not materially alter the basicand novel characteristics of the claimed composition or method.

As used herein, the singular form “a”, “an” and “the” may include pluralreferences unless the context clearly dictates otherwise. For example,the term “a compound” or “at least one compound” may include a pluralityof compounds, including mixtures thereof.

The word “exemplary” is used herein to mean “serving as an example,instance or illustration”. Any embodiment described as “exemplary” isnot necessarily to be construed as preferred or advantageous over otherembodiments or to exclude the incorporation of features from otherembodiments.

The word “optionally” is used herein to mean “is provided in someembodiments and not provided in other embodiments”. Any particularembodiment of the disclosure may include a plurality of “optional”features unless such features conflict.

Whenever a numerical range is indicated herein, it is meant to includeany cited numeral (fractional or integral) within the indicated range.The phrases “ranging/ranges between” a first indicate number and asecond indicate number and “ranging/ranges from” a first indicate number“to” a second indicate number are used herein interchangeably and aremeant to include the first and second indicated numbers and all thefractional and integral numerals therebetween. It should be understood,therefore, that the description in range format is merely forconvenience and brevity and should not be construed as an inflexiblelimitation on the scope of the disclosure. Accordingly, the descriptionof a range should be considered to have specifically disclosed all thepossible sub-ranges as well as individual numerical values within thatrange. For example, description of a range such as from 1 to 6 should beconsidered to have specifically disclosed sub-ranges such as from 1 to3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc.,as well as individual numbers within that range, for example, 1, 2, 3,4, 5, and 6 as well as non-integral intermediate values. This appliesregardless of the breadth of the range.

It is appreciated that certain features of the invention, which are, forclarity, described in the context of separate embodiments, may also beprovided in combination in a single embodiment. Conversely, variousfeatures of the disclosure, which are, for brevity, described in thecontext of a single embodiment, may also be provided separately or inany suitable sub-combination or as suitable in any other describedembodiment of the disclosure. Certain features described in the contextof various embodiments are not to be considered essential features ofthose embodiments, unless the embodiment is inoperative without thoseelements.

Although the invention has been described in conjunction with specificembodiments thereof, it is evident that other alternatives,modifications, variations and equivalents will be apparent to thoseskilled in the art. Accordingly, it is intended to embrace all suchalternatives, modifications, variations and equivalents that fall withinthe spirit of the invention and the broad scope of the appended claims.

Additionally, the various embodiments set forth hereinabove aredescribed in term of exemplary block diagrams, flow charts and otherillustrations. As will be apparent to those of ordinary skill in theart, the illustrated embodiments and their various alternatives may beimplemented without confinement to the illustrated examples. Forexample, a block diagram and the accompanying description should not beconstrued as mandating a particular architecture, layout orconfiguration.

The presence of broadening words and phrases such as “one or more,” “atleast,” “but not limited to” or other like phrases in some instancesshall not be read to mean that the narrower case is intended or requiredin instances where such broadening phrases may be absent. The use of theterm “module” does not imply that the components or functionalitydescribed or claimed as part of the module are all configured in acommon package. Indeed, any or all of the various components of amodule, whether control logic or other components, can be combined in asingle package or separately maintained and can further be distributedin multiple groupings or packages or across multiple locations.

Furthermore, embodiments may be implemented by hardware, software,firmware, middleware, microcode, hardware description languages, or anycombination thereof. When implemented in software, firmware, middlewareor microcode, the program code or code segments to perform the necessarytasks may be stored in a computer-readable medium such as a storagemedium. Processors may perform the necessary tasks.

All publications, patents and patent applications mentioned in thisspecification are herein incorporated in their entirety by referenceinto the specification, to the same extent as if each individualpublication, patent or patent application was specifically andindividually indicated to be incorporated herein by reference. Inaddition, citation or identification of any reference in thisapplication shall not be construed as an admission that such referenceis available as prior art to the present disclosure. To the extent thatsection headings are used, they should not be construed as necessarilylimiting.

The scope of the disclosed subject matter is defined by the appendedclaims and includes both combinations and sub combinations of thevarious features described hereinabove as well as variations andmodifications thereof, which would occur to persons skilled in the artupon reading the foregoing description.

What is claimed is:
 1. A method performable in a digital retail shoppingsystem including a client device in communication with a network, theclient device having a display said network connectable to a server anda database of products for purchase, the method comprising: enabling auser to browse by scrolling on the display over a list of products forpurchase using the digital retail shopping system; when the scrollingstops without a further action by the user, presenting a view of aselected product on the display; processing a personal preferencesprofile of the user; determining a comparison parameter associated withthe selected product and the personal preferences profile of the user;based on the comparison parameter, generating an advisory messagerelated to the selected product and the personal preferences profile ofthe user; and presenting said advisory message on the display of theclient device with the view of the selected product.
 2. The method ofclaim 1, further comprising: assigning the comparison parameter a weightvalue indicating a relative importance of the comparison parameter withrespect to personal preferences of the user.
 3. The method of claim 2,further comprising: based on the personal preferences of the user andthe comparison parameter of the selected product, presenting on thedisplay an alternative product, comparable to the selected product. 4.The method of claim 3, further comprising: introducing a comparisonparameter from a third party for generating an alternative product forpresenting to the user, wherein said advisory message pertains to thealternative product.
 5. The method of claim 1, further comprising:introducing a comparison parameter from a third party for selecting aproduct by the user.
 6. The method of claim 1, further comprising:retrieving a detail of a selected product from the database of productsfor purchase; when the scrolling stops without a further action by theuser, presenting the detail with the view of the selected product on thedisplay.
 7. The method of claim 1, further comprising: continuouslymonitoring user behavior and updating the personal preferences profile.8. A graphical user interface for use in a digital retail shoppingsystem, said graphical user interface enabled in a client device incommunication with a network, the client device having a display, saidnetwork connectable to a server and a database of products for purchase,wherein a detail of a selected product is retrieved from the database ofproducts for purchase, wherein a personal preferences profile of theuser is processed to determine a comparison parameter associated withthe detail of the selected product, wherein based on the comparisonparameter, an advisory message is generated related to the selectedproduct and the personal preferences profile of the user, the graphicaluser interface further configured to: enable a user to browse byscrolling on the display over a list of products for purchase using thedigital retail shopping system; when the scrolling stops without afurther action by the user, present a view of a selected product on thedisplay; present said advisory message on the display of the clientdevice with the view of the selected product.
 9. The graphical userinterface of claim 8, further configured to: assign the comparisonparameter a weight value indicating a relative importance of thecomparison parameter with respect to personal preferences of the user.10. The graphical user interface of claim 9, wherein responsive to thepersonal preferences profile of the user and the comparison parameter ofthe selected product, a view of an alternative product, comparable tothe selected product, is presented on the display.
 11. The graphicaluser interface of claim 10, further configured to: introduce acomparison parameter from a third party for selecting a product by theuser.
 12. The graphical user interface of claim 8, further configuredto: introduce a comparison parameter from a third party for generatingan alternative product for said presenting to the user, wherein saidadvisory message pertains to the alternative product.
 13. The graphicaluser interface of claim 8, wherein a detail of a selected product isretrieved from the database of products for purchase, the graphical userinterface further configured to: enable a user to browse by scrollingover a list of products on the display; when the scrolling stops withouta further action by the user, present the detail with the view of theselected product on the display.
 14. The graphical user interface ofclaim 8, wherein user behavior is continuously monitored and thepersonal preferences profile is updated responsive to the user behavioras monitored.
 15. A non-transitory computer-readable storage medium in adigital retail shopping system including a client device incommunication with a network, the client device having a display, saidnetwork connected to a server and a database of products for purchase,the computer-readable storage medium storing programming instructionsthat, if executed by a processor in the digital retail shopping system,are operable to cause the digital retail shopping system to performoperations comprising: enabling a user to browse by scrolling on thedisplay over a list of products for purchase using the digital retailshopping system; when the scrolling stops without a further action bythe user, presenting a view of a selected product on the display;processing a personal preferences profile of the user; determining acomparison parameter associated with the detail of the selected productand the personal preferences profile of the user; based on thecomparison parameter, generating an advisory message related to theselected product and the personal preferences profile of the user; andpresenting said advisory message on the display of the client devicewith the view of the selected product.
 16. The non-transitorycomputer-readable storage medium of claim 15, storing programminginstructions that, if executed by the processor, are operable to causethe computerized device to perform a further operation comprising:assigning the comparison parameter respectively a weight valueindicating a relative importance of the comparison parameter withrespect to personal preferences of the user.
 17. The non-transitorycomputer-readable storage medium of claim 16, storing programminginstructions that, if executed by the processor, are operable to causethe computerized device to perform a further operation comprising: basedon the personal preferences profile of the user and the comparisonparameter of the selected product, presenting on the display analternative product, comparable to the selected product.
 18. Thenon-transitory computer-readable storage medium of claim 17, storingprogramming instructions that, if executed by the processor, areoperable to cause the computerized device to perform a further operationcomprising: introducing a comparison parameter from a third party for:(i) selecting a product by the user; or (ii) generating an alternativeproduct for said presenting to the user, wherein said advisory messagepertains to the alternative product.
 19. The non-transitorycomputer-readable storage medium of claim 15, storing programminginstructions that, if executed by the processor, are operable to causethe computerized device to perform further operations comprising:retrieving a detail of a selected product from the database of productsfor purchase; when the scrolling stops without a further action by theuser, presenting the detail with the view of the selected product andthe detail of the selected product.
 20. The non-transitorycomputer-readable storage medium of claim 15, storing programminginstructions that, if executed by the processor, are operable to causethe digital retail shopping system to perform a further operationcomprising: continuously monitoring user behavior and updating thepersonal preferences profile.